Optimization under fuzzy if-then rules using stochastic algorithms

Jorge R. Rodríguez, María R. Méndez, Eugenio F. Carrasco

Research output: Contribution to journalArticlepeer-review


A new approach to optimization of processes described by fuzzy rules, in which the functional relationship between the decision variables and the objective function is not completely known, is introduced in this paper. It is based on stochastic algorithms and allows to determine optimal values of state variables and to optimize fuzzy rules (parameters of membership functions). Stochastic algorithms have many advantages like their robustness and, in most cases, global convergence properties. Here, a new algorithm (FICRS) was developed, being applied to the solution of a case stdy taken from the recent literature.

Original languageBritish English
Pages (from-to)181-186
Number of pages6
JournalComputer Aided Chemical Engineering
Issue numberC
StatePublished - 2005


  • fuzzy logic
  • optimization
  • stochastic algorithms


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